This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion:

What is learning?

Can a machine learn?

How to do it?

How to do it well?

Take-home lessons.

The topics in the story line are covered by 18 lectures of about 60 minutes each plus Q&A.

The course is taught by Yaser S. Abu-Mostafa. Dr. Abu-Mostafa is a Professor of Electrical Engineering and Computer Science at the California Institute of Technology. His main fields of expertise are machine learning and computational finance. He is the co-author of Amazon's machine learning bestseller Learning From Data.

Read also KDnuggets April 2013 2-part interview with Prof. Abu-Mostafa: